Surrogate models create performance predicting models based on incomplete or noisy data. They can be used to efficiently identify optimal systems settings using a limited number of experiments. The reusable components for surrogate model developed in Node-RED (developed in MATLAB) can be used in various optimization problems

The generalized drag and drop Node-RED flow gives an idea about how the Node-RED can be used for designing systems by drag and drop components and most importantly makes it possible to interface with different software tools.

UniFlex, a framework enabling uniﬁed and ﬂexible radio and network control. It provides an API enabling coordinated cross-layer control and management operation over multiple wireless network nodes. The controller logic may be implemented either in a centralized or distributed manner. This allows to place time-sensitive control functions close to the controlled device (i.e., local control application), off-load more resource hungry network application to compute servers and make them work together to control entire network.

Feature extraction script that can be used for machine learning approach for link quality estimation and prediction (for example using the Weka tool). The script uses packet reception data as input. Developed in Python.

Data set describing the UWB link quality in realistic industrial-like conditions. Traces are captured on the Wilab2 test bed by varying the position of the mobile nodes and correspondingly measure the entities: estimated signal power, estimated signal power in the first path, channel impulse response for analyzing the LOS and nLOS characteristics.

Dataset consisting of SIGFOX transmissions using different configurations (gain, frequency hopping patterns, packet repetitions) recorded at JSI campus. Radio link was from an in-door device to an out-door SIGFOX base station. Includes packet loss data, RSSI, SNR and radio spectrum recordings.